Comments (2)
JustGlowing
commented on May 28, 2024
hi @aznt00th MiniSom is minimalistic in the coding approach, not in the features implemented. However, I avoid reimplementing stuff which is easier to do in sklearn. If you have a smart way to expose the connectivity matrix, which is not just a replementation of pairwise_distance please submit a pull request.
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benjamanjiman
commented on May 28, 2024
Hey, had a look at pairwise_distance and am not confident that I fully understand whats happening there, but i believe that would give you the distances between your weight vectors in weight space directly and not be subject to the topology of the som. I think the term i actually intended to use is an adjacency matrix, not a connectivity matrix.
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Related Issues (20)
- Is there way to classify SOM based on the u-matrix ? HOT 1
- Question on topology parameter. HOT 2
- KeyError: 339
- Question on the radius. HOT 2
- About how you efficiently calculate the winner and the neighbourhood function. HOT 1
- How can I get reproducible results? HOT 2
- Meaning of the position of winning nodes and distance map HOT 3
- considerations on the hexagonal neighborhood used in `distance_map()` HOT 6
- It seems the next run will be influenced by the former run. Will it be more rational to reset after every run? HOT 4
- Is there a way to create clusters of equal size? HOT 2
- What's the order of the coordinates returned by the winner method? HOT 2
- How to save and load trained model for cluster prediction on new data? HOT 1
- PCA initialization HOT 7
- Adjacent nodes in hexagonal distance do not have distance 1 HOT 2
- unexpected problem calling the functions HOT 11
- errors in 'AdvancedVisualization.ipnyb' example HOT 2
- Help with clustering and visualization of neurons HOT 1
- There might be an index error in TimeSeries.ipynb HOT 1
- decay for sigma can be improved HOT 2
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